Genetic algorithm application for optimizing traffic signal timing reflecting vehicle emission intensity

Urbanization has created continuous growth in transportation demand, leading to serious issues, including infrastructure overload, disrupted traffic flow, and associated vehicular emissions. As a result, resolving these problems has become one of the primary missions of governments worldwide. The optimization of the traffic signal timing system is considered a promising approach to overcoming the negative consequences of increasing vehicle volume. In metropolises, oversaturated intersections, where the traffic density and vehicle exhaust emission levels are significant, have been considered as the priority to target. Several scientists have attempted to design traffic lights with the most appropriate timing. However, the majority of previous studies have not formed a comprehensive evaluation of essential factors, especially regarding the appropriate weighting of vehicle emission parameters. By assessing the all-inclusive relationship of critical elements with an emphasis on vehicle exhaust emissions, a performance index model using a genetic algorithm (GA) is established in this paper, demonstrated by data from a case study in Taiwan.